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Academic literature on the topic 'Warehouse efficiency'

Author: Grafiati

Published: 29 June 2021

Last updated: 21 June 2025

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Journal articles on the topic "Warehouse efficiency"

Vaibhavi, Chide Rajashree Dange* Gauri Darandale Chaitali Dhokane Soham Dhokte Dr. S. D. Mankar. "A Review on Good Warehousing Practices." International Journal of Pharmaceutical Sciences 3, no. 4 (2025): 3014–22. https://doi.org/10.5281/zenodo.15277548.

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Warehouse efficiency is now used by organizations as a strategic weapon or as a center of knowledge.  An efficient warehouse can help a business succeed by promptly meeting consumer needs.  Thus, this study aims to investigate the relationship between warehouse features and warehouse efficiency.  This study examines two aspects of warehouses: their design and how they are used.  This article addresses the vital need to preserve data integrity, accuracy, and dependability in contemporary organizational environments by providing a thorough framework for data quality assurance in data warehousing.  While providing recommended practices for preventing and resolving typical data quality problems such duplication, inconsistencies, missing values, and data drift, it also examines these concerns.In addition to the deployment of strong data governance structures and automated monitoring systems, the framework covers a broad variety of data quality management topics, such as data validation, reconciliation, cleansing, and enrichment procedures. First, a review of the literature was done to determine how warehouse features (operation and layout) affect warehouse efficiency so that lessons could be learned.  Additionally, a warehouse that is organized to facilitate prompt customer service is more efficient.  A major component of increasing the warehouse's efficiency is its operations, in addition to its layout.  Together, operations and layout increase a warehouse's overall efficiency.

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Islam, Md Rakibul, Syed Mithun Ali, Amir Mohammad Fathollahi-Fard, and Golam Kabir. "A novel particle swarm optimization-based grey model for the prediction of warehouse performance." Journal of Computational Design and Engineering 8, no. 2 (2021): 705–27. http://dx.doi.org/10.1093/jcde/qwab009.

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Abstract Warehouses constitute a key component of supply chain networks. An improvement to the operational efficiency and the productivity of warehouses is crucial for supply chain practitioners and industrial managers. Overall warehouse efficiency largely depends on synergic performance. The managers preemptively estimate the overall warehouse performance (OWP), which requires an accurate prediction of a warehouse’s key performance indicators (KPIs). This research aims to predict the KPIs of a ready-made garment (RMG) warehouse in Bangladesh with a low forecasting error in order to precisely measure OWP. Incorporating advice from experts, conducting a literature review, and accepting the limitations of data availability, this study identifies 13 KPIs. The traditional grey method (GM)—the GM (1, 1) model—is established to estimate the grey data with limited historical information but not absolute. To reduce the limitations of GM (1, 1), this paper introduces a novel particle swarm optimization (PSO)-based grey model—PSOGM (1, 1)—to predict the warehouse’s KPIs with less forecasting error. This study also uses the genetic algorithm (GA)-based grey model—GAGM (1, 1)—the discrete grey model—DGM (1, 1)—to assess the performance of the proposed model in terms of the mean absolute percentage error and other assessment metrics. The proposed model outperforms the existing grey models in projecting OWP through the forecasting of KPIs over a 5-month period. To find out the optimal parameters of the PSO and GA algorithms before combining them with the grey model, this study adopts the Taguchi design method. Finally, this study aims to help warehouse professionals make quick OWP estimations in advance to take control measures regarding warehouse productivity and efficiency.

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Larutama, Wiku, Dewang Rangga Bentar, Rifqy Oktavian Risdayanto, and Ridwan Salman Alvariedz. "Implementation of Warehouse Management System Planning in Finished Goods Warehouse." Journal of Logistics and Supply Chain 2, no. 2 (2022): 81–90. http://dx.doi.org/10.17509/jlsc.v2i2.62840.

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Warehouses play an important role in the supply chain by serving as a link between producers and end consumers. Warehouses not only serve as a place to store goods, but also have other important functions. Operational efficiency and logistics control in finished goods warehouses are increasingly becoming an urgent need for companies in various industries. However, ineffective warehouse management can lead to negative impacts such as decreased profits and customer dissatisfaction. Therefore, efforts are needed to manage warehouses with good efficiency and structure. This article discusses the concept of Warehouse Management System (WMS) and finished goods warehouse management in an effort to improve operational efficiency and logistics control. Through a qualitative approach with data acquisition using literature review from various relevant sources, the relationship between the use of WMS and increased productivity in a company is examined. The results showed that there was a significant improvement in the performance of a company. The WMS is proven to increase the number of orders received and the company’s operational efficiency. WMS aids inventory management with real-time stock data, preventing shortages or excesses. Successful implementation demands proper strategy, tech utilization, planning, system integration, and employee training. Thus, WMS implementation can bring about positive changes in warehouse operational efficiency, inventory optimization, and meeting customer needs.

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Kim, Thai Young, Rommert Dekker, and Christiaan Heij. "Improving warehouse labour efficiency by intentional forecast bias." International Journal of Physical Distribution & Logistics Management 48, no. 1 (2018): 93–110. http://dx.doi.org/10.1108/ijpdlm-10-2017-0313.

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Purpose The purpose of this paper is to show that intentional demand forecast bias can improve warehouse capacity planning and labour efficiency. It presents an empirical methodology to detect and implement forecast bias. Design/methodology/approach A forecast model integrates historical demand information and expert forecasts to support active bias management. A non-linear relationship between labour productivity and forecast bias is employed to optimise efficiency. The business analytic methods are illustrated by a case study in a consumer electronics warehouse, supplemented by a survey among 30 warehouses. Findings Results indicate that warehouse management systematically over-forecasts order sizes. The case study shows that optimal bias for picking and loading is 30-70 per cent with efficiency gains of 5-10 per cent, whereas the labour-intensive packing stage does not benefit from bias. The survey results confirm productivity effects of forecast bias. Research limitations/implications Warehouse managers can apply the methodology in their own situation if they systematically register demand forecasts, actual order sizes and labour productivity per warehouse stage. Application is illustrated for a single warehouse, and studies for alternative product categories and labour processes are of interest. Practical implications Intentional forecast bias can lead to smoother workflows in warehouses and thus result in higher labour efficiency. Required data include historical data on demand forecasts, order sizes and labour productivity. Implementation depends on labour hiring strategies and cost structures. Originality/value Operational data support evidence-based warehouse labour management. The case study validates earlier conceptual studies based on artificial data.

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Osman, Mohd Khidir, Effendi Mohamad, Nurhayati Kamarudin, and Arfauz A. Rahman. "Warehouse operations optimisation through the implementation of lean methodology: A comprehensive review." Multidisciplinary Reviews 8, no. 4 (2024): e2025110. http://dx.doi.org/10.31893/multirev.2025110.

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In 2022, there was a slow growth in the developing nations' GDP, but Malaysia's economy grew strongly at 8.7% due to increased activity in a number of sectors, particularly in services. Malaysia’s strong economic growth has created a higher demand for warehouse facilities and efficient warehouse operations. As a result, the need for efficient warehouse operations to reduce expenses is evident. Thus, finding the best way to structure and design warehouse operations to maximise efficiency has been a significant problem for many organisations. Consequences, such as increased waste and a negative effect on the warehouse's overall performance, are due to lack of feedback and poor selection of logistical tools to improve flow efficiency. Therefore, this article contributed to bridge the gaps of knowledge on the lean theoretical framework for warehouse operations optimisation in finished goods warehouses. The study employs a qualitative research design methodology, reviewing and analysing 7 quality journals using thematic analysis. The analysis results have classified four key factors that influence warehouse operations optimisation: warehouse layout, material flow, inventory information, and resource allocations. These critical factors of warehouse operations efficiency are significantly affected by 5 primary wastes: waiting, transportation, defect, inventory, and underutilised employees. The findings has shown that the core lean tools, VSM and 5S, should be used sequentially to eliminate waste. The tools can also be used in conjunction with other complementary lean tools to further reduce primary waste. At the end, the study's findings highlighted the framework that aligned these key elements: warehouse operations factors, waste, and lean tools as the foundation structure and design of the theoretical framework for warehouse operations optimisation through the implementation of lean methodology to enhance production and orders. This work is anticipated to establish a basis for future research in the same field as a result of its innovative discoveries.

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Enoch Oluwademilade Sodiya, Uchenna Joseph Umoga, Olukunle Oladipupo Amoo, and Akoh Atadoga. "AI-driven warehouse automation: A comprehensive review of systems." GSC Advanced Research and Reviews 18, no. 2 (2024): 272–82. http://dx.doi.org/10.30574/gscarr.2024.18.2.0063.

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This comprehensive review explores the profound impact of artificial intelligence (AI) on warehouse automation, providing an in-depth examination of various AI-driven systems. As industries increasingly embrace automation to enhance efficiency and streamline operations, the integration of AI technologies into warehouse management systems has become pivotal, reshaping the landscape of logistics and supply chain management. AI-driven warehouse automation systems leverage advanced algorithms to optimize various aspects of warehouse operations, from inventory management to order fulfillment. Machine learning algorithms play a key role in demand forecasting, allowing warehouses to predict and adapt to changing customer needs. Computer vision technologies enhance robotic vision, facilitating tasks such as item recognition, pick-and-place operations, and quality control. These advancements significantly contribute to increased accuracy, speed, and cost-effectiveness in warehouse processes. The review provides a detailed examination of the applications of AI in warehouse automation, encompassing autonomous mobile robots (AMRs), robotic arms, and automated guided vehicles (AGVs). AMRs equipped with AI algorithms navigate warehouse environments autonomously, optimizing pick routes and adapting to changes in the warehouse layout. Robotic arms, enhanced by AI, enable precise and adaptable material handling, contributing to the efficiency of tasks like packing and palletizing. AGVs, guided by AI, ensure seamless material transport within warehouses, enhancing overall operational agility. Recent trends in AI-driven warehouse automation systems underscore the dynamic evolution of this field. Edge computing solutions empower these systems to process data locally, reducing latency and enhancing real-time decision-making. Reinforcement learning algorithms enable robotic systems to learn and adapt their behavior based on changing environmental conditions, contributing to continuous improvement and efficiency gains. In conclusion, this review illuminates the pivotal role of AI in transforming warehouse automation systems, revolutionizing the way logistics and supply chain operations are conducted. The collaborative synergy between AI and warehouse automation promises to drive unprecedented advancements in efficiency, accuracy, and adaptability within the evolving landscape of modern warehouses.

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Enoch, Oluwademilade Sodiya, Joseph Umoga Uchenna, Oladipupo Amoo Olukunle, and Atadoga Akoh. "AI-driven warehouse automation: A comprehensive review of systems." GSC Advanced Research and Reviews 18, no. 2 (2024): 272–82. https://doi.org/10.5281/zenodo.11216460.

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Chen, Guifan. "Cost Efficiency and Profitability through Intelligent Warehouse: Case Study of Unmanned Warehouse “Asia One” in JD Logistics." SHS Web of Conferences 181 (2024): 03006. http://dx.doi.org/10.1051/shsconf/202418103006.

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With the general environment of consumer purchasing power and the popularity of flexible supply chains, many warehousing companies have been based on their own needs for intelligent warehouse transformation, some warehouses for a comprehensive unmanned transformation, while some through the human-machine collaboration to control storage costs. But most of these warehouses to achieve transformation are only used to store one or a class of goods, such as the medicine and equipment industry. Able to carry out a large number and multiple items stored at the same time, intelligent warehouse construction is not popular enough, this paper will be the existing large-scale intelligent warehouse working principle, efficiency results and profit costs, and other aspects of the analysis to explore the large-scale warehouse intelligent transformation can bring specific benefits to the enterprise. The representatives of large, intelligent warehouses Amazon and Jingdong’s large and unmanned warehouses have a strong benchmark. In this paper, we select Jingdong’s large, unmanned warehouse, “Asia No. 1” and explain the working process and the role of hardware and software systems to find out what advantages the operation of these machines can bring to enterprises, what the competitiveness of intelligent equipment compared with manual labor, and how to help enterprises increase benefits and reduce costs.

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Hu, Qing Ming, Dong Sheng Li, Xi Bing Li, Jian Hua Guo, and Shi Gang Wang. "Research on Storage Automation Rebuilding of Traditional Warehouse." Applied Mechanics and Materials 151 (January 2012): 544–48. http://dx.doi.org/10.4028/www.scientific.net/amm.151.544.

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A storage automation rebuilding scheme was proposed to enhance the space utilization and operational efficiency based on the analysis of the existing problem on traditional warehouse. The warehouse’s re-designing & re-planning scheme was determined, and the computer management & control system based on barcode and Radio Frequency (RP) technology was introduced with the fully utilization of traditional warehouse and original equipment. The hardware and software of the system were also expounded. Finally according to the requirement of host computer management & control system, operational control technology is integrated with information management, and the operation-oriented warehouse dynamic information management system was elaborated. The research results show that the rebuilding schemes have important theoretical and realistic significance on the improvement of changing the traditional warehouses into logistics centers.

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:Rao, Aamir Khush Naseeb, Younis Nuzhat, Hussain Sajid, and Kausar Uzma. "Next Big Thing: Voice Centric and RFID base Warehouse Management System." International Journal of Management Sciences and Business Research 2, no. 12 (2013): 01–07. https://doi.org/10.5281/zenodo.3441859.

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Warehouses are those commercial buildings which are used by the manufacturers, exporters and other companies which are providing warehouses solutions and using new technologies in material handling and following ISO standards to maintain the efficiency of the operations of the warehouse. In this paper, we investigate impact of information technology on the warehouse management system and study focus on the implementation of voice centric and Radio Frequency identification (RFID). Rest of the paper explain the basics of warehouse management system starting from type and nature of warehouses along with study of which type of warehouse management system are available to supporting manufacturing process proactively.

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Dissertations / Theses on the topic "Warehouse efficiency"

Salomonsson, Emilie. "Challenges for warehouse efficiency : A case study at a stock point warehouse." Thesis, Högskolan i Gävle, Avdelningen för industriell ekonomi, industridesign och maskinteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-36953.

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Introduction: Improving efficiency through the supply chain has long been strived for by management. Traditional approaches focus on improving efficiency in the supply chain through optimization of a company’s internal activities, where warehouses play an important role. Companies are therefore dealing with the dilemma of how to increase efficiency in their warehouse, yet at the same time reduce operational costs. Current research focuses on strategies to increase efficiency in conventional warehouses by studying design, operations, and planning. Digitalization and lean warehousing are also emerging as important tools for warehouse efficiency. However, alternative warehouse types exist that are less researched. The research aimed therefore to investigate the challenges warehouses with stock point design face. Methods: A qualitative and deductive case study approach was chosen. A literature review was first conducted to find the variables defining warehouse efficiency. Interviews and observations were then performed at the case company to investigate how the variables affect efficiency at the case company. Lastly, the theoretical framework was compared to the findings to find strategies to overcome the challenges. Findings: Efficiency problems can be found in many aspects of the case company´s warehouse. Over time the warehouse has lost its structure, where a lot of reliability for warehouse procedures are placed on the employees and their knowledge about the company and all parts. Because of missing routines for reviewing parts data, changes in generations and parts being revised, are hard to keep track of which causes an effect on efficiency. It also increases the risk of deadstock. Conclusions: In previous research, few studies could be found where researchers tackle the problems that multiple storage building causes on efficiency. By concluding that seven key variables define warehouse efficiency from previous research and applying them to a warehouse with stock point design, the challenges that an alternative warehouse face through the important variables in warehouse efficiency research could be explained. All the variables affect efficiency, yet warehouse design has the biggest impact. Because of limited abilities with hand scanners and missing routines for reviewing parts data, operations, movement, and planning can also be concluded to have a high influence on efficiency. To overcome the challenges, strategies for class-based storage assignment should be applied from the perspective of the storage building limitations. Right conditions for batching and good routines for warehouse procedures and reviewing parts data are also suggested as strategies.

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Fong, Hui Ni Grace. "Improving and maintaining the operational efficiency of a semiconductor equipment manufacturing warehouse." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101336.

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Thesis: M. Eng. in Manufacturing, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (pages 85-86). The present work addresses an operational inefficiency problem at a semiconductor equipment manufacturing warehouse, Varian Semiconductors Associates and Equipment (VSEA). This problem is important because if unresolved, the warehouse is unable to meet the part delivery time target of 24 hours during the busy period. The downstream effects of the late part delivery are delayed production schedules and in the worst case scenario, a missed shipment to the customer, which is very costly. In order to improve the efficiency of the warehouse so as to consistently deliver parts on time, the picking efficiency needs to be enhanced. Parts are primarily picked from two types of storage locations - GL shelves and Vertical Lift Modules (VLMs). The picking efficiency can be improved by the simultaneous reduction in workload on GL and improvement in the VLM picking efficiency. The first part of this thesis focuses on improving the picking inefficiency at the VLMs by employing a more efficient picking method. From our time study, we find that the pick-and-consolidate (parallel picking) is more efficient than pick-and-pass (sequential picking). The average makespan time savings per order by pick-and-consolidate is 8% (20 minutes). The second part of this paper discusses what is required to maintain a high VLM picking efficiency. New metrics to measure the workload distribution of the VLMs and the average flow time per order are proposed. Three dynamic slotting methods that maintain a balanced workload distribution across the VLMs without the need for periodic review are also examined. The methods are evaluated based on how balanced is the workload distribution across the VLMs and the cost of implementation. by Hui Ni Grace Fong. M. Eng. in Manufacturing

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Blom, Amanda, and Sofia Stenman. "Warehouse management – streamlining picking rounds." Thesis, Högskolan i Borås, Akademin för textil, teknik och ekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-25536.

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In this study we have conducted research on how to optimize inventory management within logistics. The focus in this study is to examine the picking rounds, the reason for this is because it is the most time consuming and expensive part within a warehouse. Is it possible to minimize the handling time to create efficient picking rounds? As a part of the research project AI has been investigated as well. If it is possible with help of AI, create a streamlining of current warehouse logistics. The purpose of this report is to investigate how to minimize the distance in picking rounds for efficient warehouse management. To be able to fulfil the purpose of the report research questions where conducted. The methodology that was chosen at first was traditional data collection. With the help of other studies conducted in this area we started to collect information. To be able to compare this information to the chosen company Care of Carl a case study was performed. A case study on the current situation at Care of Carl, and what the current optimization is based on. With the help of these two methods a result emerged. The result that was conducted by this study is that placement and categorization of products as well as route planning has a significant role when streamlining the picking process and minimizing the picking process. To store items in a warehouse the most suitable option is to use a free item placement, or storage out of sale frequency. But important to acknowledge is that it requires support systems to make this storage possible. When categorizing articles, it is crucial to combine this with a suiting picking method. In the case study, combining ABC categorization with zone picking was a possible solution. In general, it might be a good idea to invest in AI to use the picking position principle. With AI it is possible to analyse more complex data such as customer patterns and if this implementation succeeds it can lead to great advantages within a warehouse and the picking processes. The traveling distance constitutes most of the total picking time, it is important to have a route method that works with how you have chosen to place the items. This study shows that the optimal routing method is the one to use. This study showed that there are a lot of different strategies and methods on the current market. According to the case study Care of Carl can make big savings by changing strategies and methods. The reason why is because they have been reactive when investing in IT support systems. But in general, if a company wants to meet the current increasing requirements according to the globalization and the continuous changes within logistics operations, AI is the next step. The methods that are currently used are not sufficient, with the help of AI there is room for improvements within product allocation and route planning. I denna studie har det undersökts hur man kan optimera lagerhanteringen inom logistik. Fokus har varit att undersöka plockrundorna, då det är den mest tidskrävande och kostsamma delen inom ett lager. Är det möjligt att minimera hanteringstiden och därmed effektivisera plockrundorna? Studien har även varit en del av ett forskningsprojekt där man har undersökt om det med hjälp av AI är möjligt att skapa en effektivisering av lagerhantering. Syftet med denna rapport är att undersöka hur man minimerar avståndet i plockrundorna för att effektivisera lagerhanteringen. För att kunna uppfylla syftet med rapporten utformades det forskningsfrågor kopplat till syftet. Traditionell datainsamling var den metod som användes för att komma i gång med studien. Den teoretiska referensramen som skapades i denna rapport var utifrån andra studier som genomförts inom detta område, men även utifrån att kunna besvara de forskningsfrågor som skapats. Det genomfördes även en fallstudie på företaget Care of Carl, med en nulägesbeskrivning samt en förklaring gällande hur deras nuvarande optimering tagits fram. För att kunna besvara syftet med rapporten och forskningsfrågorna jämfördes den teoretiska referensramen med den fallstudien som genomförts i samband med denna studie. Resultatet som framkom under studien var att placering och kategorisering av produkter såväl som ruttplanering har en avgörande roll gällande effektivisering av plockprocessen i ett lager. Gällande inlagringsmetod är det lämpligast att använda sig av flytande artikelplacering alternativt lagring utifrån försäljningsfrekvens. Vad som är viktigt att nämna är att båda metoder kräver ett stödsystem för att kunna implementeras. Gällande kategorisering av artiklar är det viktigt att kombinera detta med en passande plockmetod. I fallstudien var en möjlig lösning att kombinera ABC-kategorisering med zonplockning. Generellt sätt är AI en framtida värd investering då man kan använda sig av plockpositionsprincipen. AI möjliggör analysering av mer komplexa data som kundmönster och om denna implementering lyckas kan det leda till stora fördelar inom ett lager och för plockprocessen. Det är även viktigt att ha en ruttmetod som fungerar ihop med den placeringsmetod man använt sig av, då gångtiden och gångavståndet är det som utgör det mesta av den totala plocktiden. Denna studie visar att den optimala ruttmetoden är den som bör användas, och detta kräver en investering i ett stödsystem. Denna studie visade att det för tillfället finns många olika strategier och metoder på marknaden idag. Enligt fallstudien kan Care of Carl göra stora besparingar bara genom att ändra sina strategier och metoder. Orsaken är att de har varit reaktiva vid investeringav IT-stödsystem. Generellt sätt, om ett företag vill uppfylla de ökande kraven som finns till följd av globaliseringen och de kontinuerliga förändringarna inom logistikverksamheten, är AI nästa steg att ta. Metoderna som för närvarande används är inte tillräckliga och med hjälp av AI finns det möjlighet för förbättringar inom produktallokering och ruttplanering.

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van, Hooff Jonathan, and Oscar Tegni. "Development of Supply Chain : Information System Integration at Consignment Warehouse for Improved Efficiency." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-90520.

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Sandvik Rock Tools is operating in a highly competitive market. This requires them to constantly improve the efficiency of their organization, in order for them to maintain their position as market leaders, both in a short-term and a long-term perspective. Sandvik Rock Tools is currently working on developing and further improving their supply chain. The supply chain is a key organizational function and improvements of the supply chain aim to yield benefits like lowered total costs and better utilized inventory levels. The purpose of our work has been to develop the supply chain between Sandvik’s in-market warehouse and their customer site at Dannemora. The main focus of this thesis has been to enable automatic data collection and to lower the stock levels at the customer site in Dannemora. This would be accomplished by improving the information flow between the two entities in the observed supply chain and by enabling real-time inventory information, easily accessible to the warehouse manager. A barcode system was implemented in the warehouse at the Dannemora customer site and was integrated with warehouse management software that was developed by the authors. The implemented barcode system and the warehouse management software were used at the Dannemora customer site for a period of two months. The effects of the implemented barcode system working in combination with the warehouse management software were observed in several operational areas after implementation, and the results were positive and beneficial. Firstly, the barcode system and warehouse management software simplified the warehouse manager’s decision process, by providing easy access to necessary warehouse management information, like realtime inventory information. Secondly, it made the day-to-day work routine of the warehouse manager easier, this being the case because the barcode system that had been implemented had digitalized and automated many tasks that had previously been performed manually by warehouse manager. An excellent example would be the simplified process for order placement and stocktaking. Thirdly, it improved the information flow between the Dannemora customer site and Sandvik’s in-market warehouse in Sandviken, thereby improving the overall effectiveness of the entire supply chain, through shared information. The barcode implementation successfully lowered inventory levels by six percent on average.

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Toor, Paramveer Singh. "Improving operational efficiency of a semiconductor equipment manufacturing warehouse through strategic allocation of parts." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101477.

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Thesis: M. Eng. in Manufacturing, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (page 75). The work addresses the operational inefficiency problem in a semiconductor equipment manufacturing warehouse of Applied Material's Varian Semiconductor Business Unit. At Varian, the target part delivery time from the warehouse to the production floor is 24 hours. However, during busy periods, parts are not delivered on time. Late part delivery from the warehouse to the production floor could delay the machine laydown date, which in turn could result in late or missed shipment of tools to the customers, which can be very costly. To improve the efficiency and the reliability of the warehouse, picking efficiency is to be improved. Parts from the warehouse are picked from three picking locations- Vertical Lift Modules (VLMs), GL, and RK. VLMs are automated machines, while GL and RK are manual picking zones. Picking an order from GL takes the most amount of time. The overall picking efficiency at the warehouse can be improved by partially shifting the workload from GL to the VLMs, and by further improving the picking efficiency at the VLMs. The workload from GL to the VLMs is shifted by transferring fast moving parts from GL to the VLMs. The picking efficiency of the VLMs is improved by balancing the workload of all five VLM pods, and by employing a more efficient 'pick-and-consolidate' picking strategy. The workload at GL is decreased by 25% and the workload at VLMs is increased by 13%. Despite the increase in workload at VLMs, 23% time savings could be achieved by balancing the utilization of all five VLM pods. Additional time savings of 20 minutes per order (8%) could be achieved by using 'pick-and-consolidate' picking strategy over 'pick-and-pass' picking strategy. by Paramveer Singh Toor. M. Eng. in Manufacturing

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Racca, Stephen Douglas. "Improving operational efficiency of a semiconductor equipment manufacturing warehouse through effective utilization of Vertical Lift Modules." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101335.

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Thesis: M. Eng. in Manufacturing, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (pages 59-60). This thesis deals with improving the operational efficiency of automated part storage devices, in this case Vertical Lift Modules (VLM). This was accomplished by using dynamic slotting to maximize and maintain high material throughput, eliminating the need for periodic reslotting. Multiple VLMs can be used in parallel picking operations to improve material throughput. Common industry practice is to periodically reslot items once an unbalanced workload is obvious. This thesis investigates a method to avoid periodic reslotting by using incoming parts as a means to maintain a balanced workload amongst VLMs. Three different part allocation strategies are compared, namely Randomization, Snake and Order Grouping to determine their effectiveness and respective feasibility. The three strategies are then crafted into logical systems that could be used to strategically place received parts and eliminate the need for periodic reslotting. The Snake method was found to be the most well suited for this particular situation due to the small order sizes. This method provides a 35% savings in pick time, which is equivalent to approximately 733 hours annually. by Stephen Douglas Racca. M. Eng. in Manufacturing

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Markén, Camilla, and Emma Hultqvist. "Improving the internal efficiency at IKEA After Sales focusing on the development of a warehouse management system." Thesis, Uppsala universitet, Industriell teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-329083.

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A warehouse management system shall handle warehousing operations with the aim of gaining control over the company's storage capacity and inventory management. It should support functions such as goods receiving, warehousing, order receiving and orderpicking. In order for a warehouse management system to function optimally, it must be designed for the company's operations. The purpose of this thesis work is to analyze the current warehouse management system and associated processes at IKEA After Sales. By analyzing the current situation, the improvement work will result in a development of current system or system replacement. In addition, an implementation plan will be presented for the chosen solution. The systems that have been analyzed are M3 and Astro. The research work began with a visit to IKEA After Sales where observations and interviews were conducted. The focus was on mapping how operations work today and where there is potential for a warehouse management system. A list of requirements was then presented to describe what functions a system should contain. The requirement list was discussed with responsible IT-workers for both systems. The survey showed that a lot of work is done manually and is dependent on competent employees. The research work resulted in an implementation of untapped functions in the already used system M3. The implementation plan focuses on Warehouse Mobility, inventory function and Wave Picking features with associated routines. The routines for how the business should work was designed to facilitate the workload after implementing the above functions. Ett lagersystem ska hantera lagerverksamheten med syftet att skapa kontroll över företagets lagringskapacitet och lagerhantering. Systemet bör stödja funktioner som godsmottagning, lagerläggning, ordermottagning och plockorder. För att ett lagersystem ska fungera optimalt bör det vara utformat efter företagets verksamhet. Syftet med examensarbetet är att analysera det nuvarande lagersystemet med tillhörande processer på IKEA After Sales. Genom analys av nuläget ska förbättringsarbetet resultera i en förbättring av nuvarande lagersystem eller förslag på byte av system. Vidare ska en implementeringsplan presenteras för det valda lösningsförslaget. De system som har analyserats är M3 och Astro. Examensarbetet inleddes med ett besök på IKEA After Sales där observationer och intervjuer genomfördes. Fokus låg på att kartlägga hur verksamheten arbetar idag och var outnyttjad potential för ett lagersystem finns. En kravlista framställdes för att beskriva vilka funktioner som bör finnas i ett lagersystem. Kravlistan diskuterades med respektive IT-ansvarig för systemen. Kartläggningen visade att mycket arbete sker manuellt och är beroende av kompetent personal. Resultat av examensarbetet är förslag på en implementering av outnyttjade funktioner i det redan använda systemet M3. Implementeringsplanen fokuserar på funktionerna Warehouse Mobility, stöd för inventering och Wave Picking med tillhörande rutiner. Rutinerna för hur verksamheten bör arbeta har utformats för att underlätta arbetsmomenten efter att ovanstående funktioner har implementerats.

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Khodr, Nino. "Strengthening Efficiency and Safety in Forklift Operations through Autobiographical Design." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296186.

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Forklift vehicles used for moving pallets and boxes in warehouses, have recently been integrated with Internet of Things (IoT) technology, in effect making forklifts networked and in parts controllable from afar. Human operators now carry out tasks according to instructions displayed on the screen of the IoT-forklift instead of just maneuvering around and executing tasks as they see fit. Through an autobiographical design process, hazardous situations arising because of limitations at the interface of the IoT-forklifts were revealed. To address these hazardous situations, we propose changing the interface of the forklift to better monitor the pick-up and dropping of packages. Changes to the digitally-enabled interface was done through the implementation of modalities. In short three modalities was considered, tactile, visual and auditive ones. While the tactile modality was not deemed to be feasible, the visual and auditive modalities was prototyped and evaluated through an Wizard of Oz method. Colored LED light strips showed to improve the handling, locating, selecting and moving the correct goods within the warehouse while keeping both operators and items safe. Further improvements to the digitally-enabled infrastructure in the warehouse that can optimize the routes to and from the pickup were devised. Cameras, sensors and lasers installed on advantageous places within the warehouse and on the forklift will help keeping track on both the forklift operators and the items during pick - and drop operations. As a result the system will have an awareness of its environment were both efficiency and safety will be further improved. Gaffeltruckar som används for att flytta pallar och lådor i lager har nyligen integrerats med IoT-teknologin (Internet of Things), vilket gör gaffeltruckar i nätverk och i delar kontrollerbara långt ifrån. Mänskliga operatörer utför nu uppgifter enligt instruktionerna som visas på IoT-gaffeltruckens skärm istället för att bara manövrera runt och utföra uppgifter som de anser lämpligt. Genom en självbiografisk designprocess avslöjades farliga situationer som uppstod på grund av begränsningar vid gränssnittet mellan IoT-gaffeltruckarna. För att hantera dessa farliga situationer föreslår vi att man ändrar gaffeltruckens gränssnitt för att bättre övervaka hämtning och släppande av paket. Ändringar av det digitalt aktiverade gränssnittet gjordes genom implementering av modaliteter. Kort sagt övervägdes tre metoder, taktila, visuella och auditiva. Även om den taktila modaliteten inte ansågs vara genomförbar prototyperades och utvärderades de visuella och auditiva metoderna genom en Wizard of Oz-metod. Färgade LED-ljusremsor visade sig förbättra hanteringen, lokaliseringen, valet och flyttandet av de rätta varorna inom lagret och samtidigt hålla både operatörer och föremål säkra. Ytterligare förbättringar av den digitalt aktiverade infrastrukturen i lagret som kan optimera rutterna till och från upphämtningen planerades. Kameror, sensorer och lasrar installerade på fördelaktiga platser i lagret och på gaffeltrucken hjälper till att hålla koll på både gaffeltruckoperatörema och föremålen under plock - och släppoperationer. Som ett resultat kommer systemet att känna till sin miljö där både effektivitet och säkerhet kommer att förbättras ytterligare.

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SÖDERBÄRG, KARL. "Industry 4.0 to enhance lean resource efficiency." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299625.

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This paper is a practical and empirical investigation into the relationship and overlap between the two industrial paradigms of Lean Management and Industry 4.0. This is accomplished with an in-depth case study of a goods receipt to identify Lean wastes and accompanied by a discussion on how these wastes can be eliminated by enhancing the processes and material flows with Industry 4.0 technologies. It was found that efforts to enhance a process with Industry 4.0 Technologies should be preceded by ensuring that the process can be performed in a standardized manner. After that the study recommends improved methods of data collection which enables the effective implementation of other supporting Industry 4.0 Technologies. Denna uppsats är en praktisk och empirisk utredning av relationen och samspelet mellan de två industriella paradigmen Lean Management och Industri 4.0. Till grund för det för det ligger en utförlig fallstudie av en godsmottagning för att identifiera Lean slöserier och en tillhörande diskussion om hur dessa slöserier kan elimineras genom att förbättra arbetsprocesser och materialflöden med Industri 4.0 och tillhörande teknologier. Ur det uppdagades att åtgärder för göra processer mer effektiva med dessa Industri 4.0 teknologier bör föregås av att processen kan utföras på ett standardiserat vis. När det är säkerställt så är det denna studies rekommendation att fokusera på metoder och verktyg för insamling av data vilket blir den grund som möjliggör implementering av behjälpliga och automatiserande Industri 4.0 teknologier.

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Söderbärg, Karl. "Industry 4.0 to enhance lean resource efficiency." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301241.

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Books on the topic "Warehouse efficiency"

Office, Energy Efficiency. Energy efficient lighting warehouses. Department of the Environment, 1994.

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Great Britain. Energy Efficiency Office., ed. Introduction to energy efficiency in factories and warehouses. Energy Efficiency Office, 1994.

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Vossel, Els van, Els van Vossel is the author and reviewer op OpenERP books, joint author, ed. Integrate your logistics processes with Open ERP: Efficient warehouse management with sales and Purchases Integration. Open Object Press, 2011.

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Washington State Commission for Efficiency and Accountability in Government., ed. Department of General Administartion [sic] central stores efficiency study: Final report. Washington State Commission for Efficiency and Accountability in Government, 1990.

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Ben-Mahmud, Youssef S. The effect of warehouse layout on order-picking efficiency. 1987.

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Richards, Gwynne. Warehouse Management: The Definitive Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse. Kogan Page, Limited, 2021.

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Richards, Gwynne. Warehouse Management: A Complete Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse. Kogan Page, 2021.

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Warehouse Management: A Complete Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse. Kogan Page, Limited, 2014.

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Warehouse Management: The Definitive Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse. Kogan Page, Limited, 2021.

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Warehouse management: A complete guide to improving efficiency and minimizing costs in the modern warehouse. 3rd ed. Kogan Page, 2018.

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Book chapters on the topic "Warehouse efficiency"

McGinnis, Leon, Michael Schmidt, and Detlef Spee. "Model Based Systems Engineering and Warehouse Design." In Efficiency and Innovation in Logistics. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01378-7_12.

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Vorontsov, V. B., I. A. Puzanova, and B. A. Anikin. "Energy Efficiency of the Warehouse Complex." In Proceedings of the International Scientific Conference “Smart Nations: Global Trends In The Digital Economy”. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94873-3_53.

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Abbasi, Maryam, José Silva, Paulo Váz, and Pedro Martins. "Enhancing Data Warehouse Efficiency Through Multi-tenancy." In Smart Innovation, Systems and Technologies. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3081-3_18.

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Zajac, Pawel. "Indicators and Measures of Energy Efficiency the Warehouse." In The Energy Consumption in Refrigerated Warehouses. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40898-9_2.

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Zając, Paweł. "Model of Forklift Truck Work Efficiency in Logistic Warehouse System." In EcoProduction. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07287-6_33.

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Priyanga, S., K. Kannan, S. Deva, and R. Thamodiran. "A study on efficiency and effectiveness of warehouse management system." In Recent Research in Management, Accounting and Economics (RRMAE). Routledge, 2024. https://doi.org/10.4324/9781003606642-33.

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Berkdemir, Gizem, Gizem Atak, and Ferhan Çebi. "Warehouse Planning for Maximum Area Efficiency in the White Goods Sector." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62784-3_51.

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Fotso Mtope, Franck Romuald, Sina Joneidy, Diptangshu Pandit, and Farzad Pour Rahimian. "Multi-Aspectual Knowledge Elicitation for Procurement Optimization in a Warehouse Company." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.36.

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Efficient optimization of business processes required a profound understanding of expertise provided by domain specialists. However, extracting such insights can indeed be a laborious and time-consuming endeavour. This paper introduces the Multi-Aspectual Knowledge Elicitation framework (MAKE4ML) — a novel approach designed to effortlessly and effectively extract valuable information from domain experts. This framework inherently facilitates the development of machine-learning models capable of optimizing business processes, thereby diminishing reliance on experts. The framework's application within a food warehouse company is showcased, specifically targeting the enhancement of the procurement process. The employed methodology revolves around conducting comprehensive interviews with procurement experts, thereby enabling a meticulous exploration of diverse facets inherent to a business process. Subsequently, the gathered insights are employed to conceive and calibrate a machine learning model (time series forecasting). This model effectively emulates the domain experts' proficiency, offering invaluable decision-oriented insights. The outcomes of this study show that our framework allows efficient knowledge elicitation, which is a pivotal factor in formulating and deploying a bespoke machine-learning model. The proposed approach can be extended into various other business processes, thereby paving the way for operational refinement, cost reduction, and amplified efficiency

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Setiawan, Budi. "Implementation of SISTRO (Truck Scheduling System) to Enhance Supply Chain Efficiency and Performance to Support Industrial Revolution 4.0 in Petrokimia Gresik." In Proceedings of the 19th International Symposium on Management (INSYMA 2022). Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-008-4_133.

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AbstractSISTRO, a truck scheduling and management system, was developed to optimize stock fulfillment following the government regulation (Peraturan Menteri Perdagangan/Permendag) and the distribution process of subsidized fertilizer from Gresik Warehouse of PT Petrokimia Gresik (PG) to Buffer Warehouse located in almost every province in Java Island. The volume that must be distributed is around 5.4 million tons of fertilizer/year. During the implementation, a critical problem is the lack of integration and single information about the supply chain and truck loading process. The information includes (1) truck arrival delay, (2) the difference between planning and reality, and (3) the availability of workers. These three pieces of information are out of sync, so they have direct and indirect impacts. The direct impact is the potential for unscheduled open storage (OPS) in Gresik warehouse. At the same time, the indirect impact is the high logistics costs in the form of land transportation cost increases every year and the potential to lose the opportunity/moment to sell goods due to delays in fertilizer distribution. Therefore, a solution is needed by creating an integrated system to accommodate related parties in truck schedule arrivals, stock availability, and labor availability in the loading line warehouse, hereinafter referred to as SISTRO. The SISTRO’s scope of work starts from the distribution of quota allocations for heavy loading that has been adjusted to stock conditions and loading capacity in each warehouse so that the truck vendors can book the loading plan according to the schedule they want, based on the POSTO that has been uploaded on the SISTRO application and partners will get a booking code. The booking code will later be printed as a security pass. The security pass will later be scanned at all SISTRO checkpoints, which is proven can reduce the number of late arrivals for trucks to load appropriately from an average of 1.361 events/month to just 553 events/month. This project impacts several sectors, including reducing the risk of losing chances to sell goods that previously averaged 24,034 tons/month equivalent to Rp. 110 billion/month, a decrease in the OPS quantity (which is currently happening due to oversupply that does not match with quantum distribution). There has been no increase in inland transportation costs for 3 years and monitoring all license numbers and transportation partners so that there is no combined number of registration numbers. In fact, SISTRO can be used by all logistics companies.

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Conference papers on the topic "Warehouse efficiency"

Wu, Anxiong, and Chih-Chiang Fang. "Enhancing data warehouse efficiency through basic statistical function maintenance." In Third International Conference on Algorithms, Network and Communication Technology (ICANCT 2024), edited by Fabrizio Marozzo. SPIE, 2025. https://doi.org/10.1117/12.3059716.

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Elsawy, Arwa, Noha Warda, and Mohamed Ghoneimy. "Improving Warehouse Efficiency with Dynamic Slotting Optimization Using Genetic Algorithm." In 2025 International Conference on New Trends in Computing Sciences (ICTCS). IEEE, 2025. https://doi.org/10.1109/ictcs65341.2025.10989429.

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De Abrew, Raduni, Chathumi Kavirathna, Annista Wijayanayake, and Kasuri Abhilashani. "Efficiency Evaluations in 3PL Warehouse Operations: Building Research Themes Through Systematic Literature Review." In 2025 5th International Conference on Advanced Research in Computing (ICARC). IEEE, 2025. https://doi.org/10.1109/icarc64760.2025.10963271.

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Yu, Dezhi, Lipeng Liu, Siye Wu, et al. "Machine Learning Optimizes the Efficiency of Picking and Packing in Automated Warehouse Robot Systems." In 2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE). IEEE, 2025. https://doi.org/10.1109/eespe63401.2025.10986975.

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Hossain, Toushif, Riyad Hossain, Rubaiyat Islam, and Saadia Binte Alam. "Optimizing Warehouse Operations in Bangladesh: Leveraging IoT and Cloud Migration for Enhanced Security and Efficiency." In 2024 11th International Conference on Future Internet of Things and Cloud (FiCloud). IEEE, 2024. http://dx.doi.org/10.1109/ficloud62933.2024.00061.

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Dakun, Zheng, Li Xiang, Liu Xue, Cai Ziyu, and Wu Yihong. "Warehouse Cargo Visual Positioning and Storage Efficiency Improvement Analysis Based on Adaptive Generalized S-Transform Algorithm." In 2024 International Conference on Computers, Information Processing and Advanced Education (CIPAE). IEEE, 2024. https://doi.org/10.1109/cipae64326.2024.00108.

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Belbachir, Assia, Antonio Ortiz, Erik Hauge, et al. "Drone Technology for Efficient Warehouse Product Localization." In 21st International Conference on Informatics in Control, Automation and Robotics. SCITEPRESS - Science and Technology Publications, 2024. http://dx.doi.org/10.5220/0012947900003822.

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Amadeo, Adriel Justin, Andryan, Joyceline Graciella Siento, Putu Devi Ariska Pramunita, Vanessa Aprily Hongastu, and Kartika Purwandari. "A Web-Based Application Development for Efficient Warehouse Management." In 2024 International Conference on Information Technology Systems and Innovation (ICITSI). IEEE, 2024. https://doi.org/10.1109/icitsi65188.2024.10929443.

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Berković, Mirza. "Warehouse facility energy efficiency assessment model." In INTERNATIONAL CONFERENCE ON ADVANCES IN TRAFFIC AND COMMUNICATION TECHNOLOGIES. University of Sarajevo - Faculty of Traffic and Communications, 2022. http://dx.doi.org/10.59478/atct.2022.24.

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The aim of this paper is to investigate the formal structural elements of the energy efficiency assessment system of a warehouse facility as part of a complex distribution system. The problem of work starts from the fact that there is still no single method of assessing the energy efficiency of warehouse facilities that would unequivocally evaluate the planned and taken corrective measures, given the lack of methods related to such intensive construction. In this paper, we determine the final consumption systems of the warehouse facility and the supply systems of the warehouse facilities. The goal of a successful assessment model is to look at the financial and environmental benefits of individual measures, point out the possibilities of reducing costs and the cost-effectiveness of investing in energy efficiency measures of warehouse facilities. A successful assessment model should create the preconditions for determining clear economic criteria when setting priorities for the implementation of energy efficiency measures. The research findings show that it is possible to significantly improve the procedure for assessing the energy efficiency of warehouse facilities.

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Andar, Jakub, and Jakub Dyntar. "Efficient Order Picking in a Warehouse with Double Demand Seasonality." In Liberec Economic Forum 2023. Technical University of Liberec, 2023. http://dx.doi.org/10.15240/tul/009/lef-2023-37.

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In this paper we highlight the advantages of adopting a broad simulation model of material flows as a useful foundation for developing system support for warehouse procedures that use WMS. The warehouse under consideration has a rectangular shape with parallel lanes and operates in two distinct seasons, necessitating different storage methods. The modified simulation model incorporates several strategies to enhance efficiency. Firstly, the S-shape routing technique is employed to optimize the movement of order pickers within the warehouse, minimizing travel time and increasing productivity. Additionally, a return technique is integrated to minimize empty travel distance, further reducing operational costs. Storage assignment within the warehouse is determined based on the frequency of item occurrence and the required storage technology. To establish an effective layout for each season, the study examines historical demand data and utilizes ABC analysis to classify goods. This dual layout design approach accounts for the unique demand patterns of each season, enabling the warehouse to maximize storage capacity and minimize operational bottlenecks. By considering elements such as seasonal demand, storage technologies, labor routing, and product classification, this research provides valuable insights for improving order picking efficiency, reducing costs, and enhancing customer service in seasonal warehouses. Implementing the proposed simulation-based technique can empower businesses to optimize their operations and thrive amidst changing market conditions, ultimately leading to increased profitability and customer satisfaction.

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Reports on the topic "Warehouse efficiency"

Bianchi, Carlo, M. Rois Langner, Vedyun Mishra, and Paul Torcellini. Accelerating the Adoption of Energy Efficiency and Renewables in Warehouses and Distribution Centers. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/1909580.

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Lekov, Alex, Lisa Thompson, Aimee McKane, Alexandra Rockoff, and Mary Ann Piette. Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/962214.

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Academic literature on the topic 'Warehouse efficiency'

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Reports on the topic "Warehouse efficiency"